2026-10-17 22:01:07
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📊 Monthly reports: 200+ companies visualized.
📩 Tuesday articles: Exclusive deep dives and insights.
📚 Access to our archive: Hundreds of business breakdowns.
📩 Saturday PRO reports: Timely insights on the latest earnings.
Today at a glance:
🔬 ASML: Demand Reaches 2030
💊 J&J: MedTech Needs Work
💼 UnitedHealth: Turnaround Broadens
🇺🇸 Bank of America: Fine Masks NII Growth
👔 Morgan Stanley: IPOs Feed Wealth
📈 BlackRock: Fee Growth Hits 11%
🏦 Schwab: Lending Boom
🍕 Domino’s: Orders Up, Check Down
ASML’s Q3 revenue surged 55% Y/Y to a record €11.7 billion (€70 million miss), while GAAP EPS reached €12.93 (€2.14 beat). The EPS beat was partly flattered by a €0.5 billion valuation gain on ASML’s investment in Mistral AI, but the underlying quarter was still impressive. Gross margin reached a record 57%, well above guidance, as high-margin upgrades pushed Installed Base Management sales to €3.3 billion.
The biggest insight was how far out the AI capacity cycle has moved. Customers are increasingly placing orders for 2028 and asking ASML to accept orders for 2029 and even 2030. Management now says its currently planned supply will not fully meet demand in either 2027 or 2028. That is remarkable because ASML already planned to increase Low-NA EUV and immersion DUV capacity by roughly 30% in 2027, followed by another ~30% increase in 2028. It is now exploring an even larger ramp in 2028.
The demand is increasingly broad:
Memory system sales are expected to grow ~75% in FY26, driven largely by DRAM capacity and greater EUV adoption.
Advanced logic is growing more than 25%, even though total logic growth is closer to 10%.
EUV sales should grow more than 45% this year, while Installed Base Management is now expected to grow roughly 50%.
ASML shipped 113 new lithography systems in Q3, up from 86 in Q2.
ASML has now secured price increases on some of its most critical high-volume tools. Management expects the benefit to begin showing up in 2027 and become fully visible in 2028. Management stressed this isn’t opportunistic annual repricing, but it does confirm that ASML can capture more of the value its bottleneck technology creates.
High-NA is moving closer to actual production. Intel has now processed more than one million wafers using High-NA, Samsung plans high-volume adoption in 2028, and TSMC now targets 2030. ASML expects High-NA usage to expand node by node as customers validate the economics.
China remains the geopolitical wildcard. It represented 23% of Q3 system sales, while ASML still expects roughly 20% of full-year revenue from China. Management argues underlying Chinese demand remains strong, but further restrictions on immersion DUV could eventually accelerate development of domestic alternatives.
ASML raised FY26 revenue guidance again to €44–€45 billion (from €43–€45 billion) and now expects a gross margin of roughly 56%.
Takeaway: ASML has moved from ramping capacity to figuring out how much further it can stretch the supply chain. Customers are already signaling demand into 2030, while pricing increases and High-NA add further upside. Now it’s about ASML’s ability to build enough machines.
2026-10-16 20:02:01
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Financing is the latest obstacle in the AI infrastructure boom.
CoreWeave shares plunged more than 15% on Wednesday, while yields on some of its bonds have climbed above 16%, a level associated with distressed debt. The NVIDIA-backed cloud provider has taken on tens of billions of dollars in debt to build the data centers powering the AI boom.
The pressure extends beyond CoreWeave. Oracle and other AI infrastructure companies have also faced selling pressure as investors reassess their borrowing costs and capital requirements. Higher interest rates make an already expensive buildout even more costly.
For highly leveraged AI infrastructure providers, the concern is shifting from demand for computing power to the cost of supplying it. Companies are committing enormous amounts of capital today against revenue they expect to collect over many years.
NVIDIA CEO Jensen Huang pushed back on Thursday, insisting that CoreWeave’s financial position is improving. But NVIDIA owns roughly 10% of CoreWeave and is also one of its biggest suppliers. Huang has every incentive to defend its expansion, even as bond investors demand higher returns to finance it.
Today at a glance:
⚡ TSMC is not slowing down
🤖 The model race heats up
🏠 Apple moves into the living room
Its US-listed shares have returned more than 100x since 1997.
I put together a free 35-page report on what to look for in quality stocks before they become obvious.
Taiwan Semiconductor (TSMC) is investing at a scale few companies can match. Its CapEx budget has climbed from $41 billion in 2025 to $60–$64 billion in 2026, with cumulative spending over 2026–2028 expected to substantially exceed the previous three years.
CEO C.C. Wei has little interest in leaving opportunities to competitors:
“We have no intention to leave food on the table for others, and we want to capture every piece of business possible.”
Another record quarter backs his conviction. Q3 Revenue grew 41% Y/Y to $46.7 billion, and operating margin reached nearly 59%. TSMC is becoming more profitable even as it undertakes the largest manufacturing expansion in its history.
Income statement:
Revenue +41% Y/Y to $46.7 billion ($0.9 billion above the high end of guidance).
Gross margin 66% (-1pp Q/Q).
Operating margin 59% (+8pp Y/Y).
EPS per ADR $4.60 (+69% Y/Y in local currency).
Cash flow:
Free cash flow margin: 32% (+18pp Y/Y).
Balance sheet:
Cash and marketable securities: ~$126 billion.
Interest-bearing debt: ~$32 billion.
Guidance:
Management raised its FY26 revenue growth outlook to approximately 44% in USD, up from slightly above 40%. Q4 guidance of $52.3–$54.3 billion implies 58% Y/Y growth at the midpoint, a sharp acceleration.
🤖 AI demand keeps surprising management. TSMC previously forecast mid-to-high-50% annual growth in AI accelerator revenue through 2029. C.C. Wei now suggests even that ambitious forecast could prove conservative:
“The demand is extremely robust. We did not see any sign of slowdown. Whether it is a high 50 CAGR, it does not matter. It probably will be higher.”
The forecast excludes conventional CPUs and networking chips, which are also benefiting from the rise of AI agents. TSMC’s opportunity extends well beyond GPUs, as its changing revenue mix shows. HPC (High Performance Computing) now accounts for 68% of revenue, up from 42% just three years ago.
🏗️ TSMC wants every available order. Yet the company isn’t simply taking its customers’ forecasts at face value. It checks their financial strength, visits data center construction sites, and verifies electricity availability before committing additional capacity. These checks help explain why management remains confident enough to invest tens of billions in factories that take years to build. They also connect directly to the financing concerns facing some AI infrastructure providers.
⚙️ Manufacturing leadership comes at a cost. The new 2nm process already accounts for 8% of wafer revenue, with capacity expected to more than double by 2027. Alongside advanced packaging and 3nm expansion, this reinforces TSMC’s position as the preferred manufacturer for the most demanding chips. However, the initial 2nm ramp contributed to the sequential decline in gross margin. Overseas expansion will add further pressure, with international factories expected to dilute consolidated gross margin by 3–4 percentage points over the next few years.
💰 How profitable can TSMC become? Despite rising investment and manufacturing costs, operating margin has climbed to nearly 59%. When asked about the longer-term potential, Wei replied:
“There is no ceiling for TSMC’s profitability. But a dramatic increase will not happen overnight either.”
TSMC’s technological lead and scarce capacity give it considerable pricing power. But management is also warning that rising component costs and macroeconomic uncertainty are hurting price-sensitive consumer markets. The company enters 2027 with exceptional AI demand, but not every part of the semiconductor industry is seeing the same conditions.
Google and Meta made major moves in the AI model race this week, challenging OpenAI and Anthropic's perceived lead.
Google launched Gemini 4 Argon, its latest frontier model, claiming leadership across several benchmarks involving coding, finance, law, and cybersecurity. Its performance on professional tasks (Vals Index) is particularly noteworthy as AI agents move beyond answering questions to performing actual work.
Argon is available through Google’s API, Gemini app, Search, and coding tools. Google can distribute increasingly capable AI to billions of existing users, an advantage over independent AI labs that must build their own distribution.
Meanwhile, Meta introduced Muse Wonder and Muse Wonder Full, its most capable models to date. After struggling to keep pace at the frontier, Meta claims competitive performance with OpenAI and Anthropic. The models emphasize memory and the ability to carry out complex, multi-step tasks. Meta plans to bring these capabilities to its Muse personal AI agent.
More competition could pressure model pricing, while more capable agents could increase computing demand. Unlike chatbots that answer individual questions, agents can work through lengthy tasks involving dozens or hundreds of steps, consuming far more tokens along the way.
Better models and lower pricing don’t necessarily mean less infrastructure spending. They could make AI useful enough to justify even more investment.
Apple unveiled HomeView, a $299 smart-home display arriving November 13. It’s built around an upgraded Siri, alongside new HomePod and Apple TV devices. The seven-inch display recognizes household members and draws on personal information from their iPhones to answer questions and handle everyday tasks.
Apple also introduced cameras, thermostats, and smart locks developed with LG and Schneider Electric. These accessories work directly through Apple Home, without separate apps or accounts. The new Apple TV adds far-field microphones for hands-free Siri commands.
Apple is betting that its hardware ecosystem and access to personal data can make Siri the default interface for the connected home. But there’s a catch: HomeView still relies on a nearby, recently unlocked iPhone for personalized features, and many of its use cases already work on the phone itself.
The real test is whether Apple’s integration can compensate for Siri’s limitations. Amazon and Google already have established smart-home ecosystems, while AI agents are becoming increasingly capable of handling tasks without traditional apps.
That's it for today.
Happy investing!
Disclosure: I own AAPL, AMZN, GOOG, META, and TSM in App Economy Portfolio. I share my ratings (BUY, SELL, or HOLD) with App Economy Portfolio members.
Author's Note (Bertrand here 👋🏼): The views and opinions expressed in this newsletter are solely my own and should not be considered financial advice or any other organization's views.
2026-10-13 23:55:39
Welcome to the Premium edition of How They Make Money.
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In case you missed it:
A new earnings season is here, with the big banks kicking us off.
Later this week, we’ll have a look at TSMC and ASML for our first signals from the AI infrastructure boom.
AI is already making waves in banking. JPMorgan CEO Jamie Dimon warned today about letting AI agents access customer accounts:
“If people are using them, they should understand the risk. […] We’re not going to allow just any outside agent to come in inside the company because that’s just too risky for clients and for JPMorgan.”
The concern goes beyond security. AI agents could eventually help consumers move their money between banks, threatening the cheap deposits that underpin their profitability. Wells Fargo CEO Charlie Scharf dismissed fears of an imminent disruption as “completely overdone.”
Four banking giants just reported $32 billion in combined quarterly profits this morning. Trading momentum is becoming uneven, but lending growth and resilient consumers continue to support earnings.
Let’s break down the results.
Today at a glance:
JPMorganChase: Lending Takes the Lead
Goldman Sachs: Equities Steal the Show
Wells Fargo: Bigger Isn't Better Yet
Citigroup: Turnaround Gains Ground
Did you miss it? I put together a guide to finding quality stocks with 100x potential.
As a reminder, banks make money through two main revenue streams:
💵 Net Interest Income (NII): The difference between interest earned on loans (like mortgages) and interest paid to depositors (like savings accounts). It’s the primary source of income for many banks and depends on interest rates.
👔 Noninterest Income: The revenue from services unrelated to interest. It includes fees (like ATM charges), advisory services, and trading revenue. Banks relying more on noninterest income are less affected by interest rate changes.
Here are the significant developments shaping Q3 FY26:
📊 The trading boom splits: Equities remain on fire, led by Goldman Sachs (+72% Y/Y) and JPMorgan (+49%). But fixed-income trading declined at both banks as higher bond yields weighed on activity. Citi bucked the trend with 4% growth. Wall Street’s trading windfall is becoming increasingly uneven.
🏦 Higher rates cut both ways: JPMorgan raised its FY26 net interest income outlook to $106.2 billion, while Citi also lifted its guidance. Wells Fargo, however, held its outlook unchanged. Higher rates support lending income but also raise funding costs and create losses on existing bond holdings.
💳 Consumers keep spending: Card spending grew 10% at JPMorgan and 13% at Citi, while credit losses remained manageable across the group. Businesses are also holding up, supported by strong balance sheets and investment in AI infrastructure. Despite sticky inflation and higher borrowing costs, the anticipated credit deterioration has yet to materialize.
🎯 Profitability takes center stage: Citi raised its FY26 return target above 11% as its restructuring delivers results. Wells Fargo continues expanding its balance sheet after the removal of its asset cap, but revenue growth remains modest. The next challenge is converting growth into sustainable profits without letting expenses or funding costs erode the gains.
🔑 Takeaway: The banks are still growing, but the easy gains from the capital-markets boom are fading. Strong lending activity and healthy credit provide a solid foundation, while the divergence in trading and margins highlights how differently each franchise is positioned. Can earnings growth outlast the unusually favorable conditions of the past few quarters?
Let’s visualize them one by one and highlight the key points.
Net revenue grew 8% Y/Y to $50.2 billion ($0.3 billion miss):
Net interest income (NII): $27.0 billion (+13% Y/Y).
Noninterest income: $23.1 billion (+3% Y/Y).
Net income: $15.3 billion (+6% Y/Y).
Adjusted EPS: $5.75 ($0.19 miss), excluding $658 million in investment securities losses. Reported EPS was $5.57.
Key developments:
📉 Trading momentum fades: Trading revenue grew 15% Y/Y to $10.3 billion but missed expectations. Equities surged 49% to $5.0 billion, JPMorgan’s best third quarter ever, while fixed-income trading declined 4% to $5.4 billion. Investment banking fees rose 14% to $3.0 billion but fell sequentially as dealmaking slowed in September. Wall Street activity is cooling after an exceptional Q2.
🏦 Interest income surprises: NII rose 13% to $27.0 billion, prompting JPMorgan to raise its FY26 outlook to ~$106.2 billion (from ~$105.5 billion). Management also introduced a 2027 base case of ~$107 billion in NII excluding Markets, up ~10% from its FY26 estimate of $97.2 billion on the same basis. Loan growth and higher rates are strengthening the bank’s core earnings engine.
💳 Consumers remain resilient: Consumer banking revenue grew 9% to $21.2 billion, helped by 10% growth in card spending. JPMorgan added more than 650,000 net new checking accounts. The card net charge-off rate improved to 2.91% (from 3.34% in Q2), while management maintained its FY26 forecast of ~3.2%.
⚠️ Credit quality holds up: Credit-loss provisions fell 19% Y/Y to $2.7 billion, while net charge-offs declined to $2.2 billion. Consumer loan charge-offs improved to 1.27% (from 1.42% in Q2), while wholesale losses remained low at 0.11% (from 0.10%). However, JPMorgan added $452 million to wholesale reserves, reflecting loan growth and some changes in borrower credit quality.
💰 Buybacks slow sharply: JPMorgan repurchased just $1.1 billion of stock (from $6.7 billion in Q2), despite its new $50 billion authorization. Management favors investing in the franchise and supporting client lending over repurchases. With a 13.9% CET1 ratio, the slowdown appears to be a capital allocation choice rather than a constraint.
📈 Wealth management expands: Revenue rose 14% to $6.9 billion, supported by $263 billion in client asset net inflows. Assets under management reached $5.2 trillion (+13%), while total client assets climbed to $7.9 trillion (+15%). Growing fee-generating assets help diversify earnings beyond lending and trading.
💸 Expenses keep rising: Costs increased 12% to $27.3 billion, prompting JPMorgan to raise FY26 adjusted expense guidance to ~$108.6 billion (from ~$107.5 billion). Higher compensation, technology, and marketing spending drove the increase. Costs are growing faster than revenue, pressuring operating leverage despite healthy business activity.
🔑 Takeaways: JPMorgan’s earnings miss reflects weaker capital markets activity rather than broad deterioration. Rising NII, resilient consumers, and continued loan growth provide an offset. The decision to sharply reduce buybacks suggests management sees more attractive opportunities to deploy capital within the business.
Key quote:
CEO Jamie Dimon:
“Large fiscal deficits, sticky inflation, elevated asset prices, rising interest rates and geopolitical conditions continue to shift under the surface.”
2026-10-10 22:04:00
Welcome to the Saturday PRO edition of How They Make Money.
Over 300,000 subscribers turn to us for business and investment insights.
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📊 Monthly reports: 200+ companies visualized.
📩 Tuesday articles: Exclusive deep dives and insights.
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📩 Saturday PRO reports: Timely insights on the latest earnings.
Today at a glance:
🥤 PepsiCo: International Takes Over
🛩️ Delta: Fuel Eats the Upside
🍺 Constellation: SpikedAde Joins the Mix
🌿 Tilray: BrewDog Carries Growth
PepsiCo’s Q3 revenue rose 6% Y/Y to $25.3 billion ($310 million beat), with core EPS of $2.34 ($0.04 beat). Organic revenue growth accelerated to 3.1%, its fastest pace since late 2023, helped by 3% beverage volume growth and 1% food volume growth.
The divergence between North America and the rest of the world keeps widening:
International organic revenue grew ~8%, with EMEA up 9%. International now generates roughly 45% of PepsiCo’s profit year-to-date.
North American Foods sales were flat, though volumes improved to low-single-digit growth after last year's declines.
North American Beverages weakened, with CEO Ramon Laguarta admitting PepsiCo is “not competing well in soft drinks,” even as hydration and energy remain stronger.
GLP-1s and changing eating habits are pushing PepsiCo toward smaller portions and more protein- and fiber-focused products. Its “permissible” portfolio (better-for-you snacks) has already grown to roughly $3 billion, but it remains small relative to the traditional snack business under pressure.
PepsiCo also has an execution problem in its home market. Management plans to increase brand investment while cutting structural costs, and it is even open to selling more of its company-owned bottling operations to independent partners, making the business less capital-intensive.
Margins are getting harder to protect. Core operating profit grew 3%, but a $178 million tariff refund added roughly four percentage points to operating profit growth. Commodity costs are rising as hedges roll off, while PepsiCo is deliberately maintaining higher advertising spending to rebuild momentum.
PepsiCo now expects about 3% organic revenue growth in FY26, while cutting core constant-currency EPS growth to 2.5%–3.5% (from 4%–6%).
Takeaway: International is increasingly carrying PepsiCo while the North American turnaround takes longer than expected. With costs rising and US execution still uneven, management is moving beyond price tweaks toward a broader cost and operating-model reset.
2026-10-09 20:04:35
Welcome to the Free edition of How They Make Money.
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A 100-bagger is a stock that returns 100 times your initial investment.
Put in $10,000 and, eventually, you have $1 million.
Naturally, most investors focus on the first challenge: finding one.
But that is only half the battle.
In his book 100 to 1 in the Stock Market, Thomas Phelps showed how long it takes for compounding to turn an investment into a 100-bagger.
A stock compounding at 20% annually needs roughly 25 years to return 100 times your money. Even at an extraordinary 36% annual return, it still takes about 15 years.
And time is only part of the challenge.
Over those 15, 20, or 30 years, even the greatest winners can suffer brutal drawdowns. Apple endured repeated declines of more than 25% on its way to becoming a massive long-term winner, including two drops of roughly 80%.
Finding the right company is hard.
Holding it for 15, 20, or 25 years may be even harder.
I put together a free 35-page report on how to identify potential 100-baggers before they become obvious.
You will learn the following:
📊 What to look for
💯 A history of 100-baggers
🔎 Why they’re so hard to find
🧠 The mindset required to hold one
✅ A practical 100-bagger checklist
A stock appreciates over time through two main forces:
Earnings growth: The business makes more money.
Multiple expansion: Investors pay more for each dollar of earnings.
Over long periods, earnings do most of the work. But exceptional companies can benefit from both. As profits compound and the market finally piles in, the valuation can get overextended.
That success creates the temptation to sell.
Once a stock has doubled or tripled, our natural instinct is to lock in the gains. If the valuation has expanded along the way, selling can feel even more prudent.
But extraordinary returns are heavily back-loaded. At a 20% annual return, an investment goes from roughly 38x after 20 years to nearly 100x after 25.
Those final five years create more wealth than the first 20 combined.
That is why selling a great company too early can be one of the most expensive mistakes an investor makes. Peter Lynch famously described this as “cutting the flowers and watering the weeds.”
The best businesses have a habit of repeatedly exceeding expectations. What looks expensive today can look much more reasonable several years later if earnings keep compounding.
Selling also creates another problem.
What do you buy instead? And when do you get back in?
None of this means you should never sell. If the competitive position deteriorates, earnings falter, or the original thesis breaks, the decision changes.
But I’ve adopted a simple rule:
A rising stock price is never a reason to sell on its own.
Compounding is beautiful. You have to resist the urge to interrupt it.
Stock returns are not evenly distributed.
In statistics, you’ll hear about two common patterns:
Normal distribution: Most observations cluster around the average, while extreme outcomes are rare. Think human height or many natural measurements.
Power law distribution: A small number of extreme outcomes account for a disproportionate share of the total. Think wealth, company size, or venture returns. Extreme outcomes occur far more often than under a normal distribution, creating a fat tail.
Investing follows the power law. More than a century of market history shows that a relatively small number of stocks have created a disproportionate share of long-term wealth.
That is why constantly rebalancing can work against you.
If one stock compounds much faster than the rest, it will naturally become a larger part of the portfolio. That concentration can feel uncomfortable and make the portfolio look weird.
But it may simply be the consequence of owning something exceptional.
If you repeatedly trim your best performers, you risk systematically cutting exposure to the very companies that can make the portfolio outperform.
Warren Buffett has famously allowed investments such as Coca-Cola and American Express to become very large positions rather than continually trimming them. Apple eventually grew to nearly half of Berkshire’s listed stock portfolio before Buffett began meaningfully reducing the position.
Robert Kirby captured the same idea with his Coffee Can Portfolio.
He once discovered that a client’s husband had quietly copied each of his stock recommendations, investing about $5,000 in every company. But with one crucial difference: he never sold.
Years later, the portfolio contained plenty of mediocre investments. But one position had grown so dramatically that it was worth more than the rest of the portfolio combined.
Kirby described the approach as being “passively active.”
Active: Do the work upfront. Select the businesses carefully and decide what deserves your capital.
Passive: Once you own them, give them time to compound.
Long-term investing demands active selection followed by patient ownership.
I can see that distribution clearly in App Economy Portfolio, the real-money portfolio I’ve shared publicly for the past decade.
A dozen holdings have compounded 5x, 10x, or 20x.
That creates a powerful asymmetry. Without leverage, a loser can cost you at most 100% of your investment. But a 10x or 20x winner can more than offset many losers.
You can see that in the visual below. Even holdings that were nearly wiped out look small next to the biggest winners.
AMD is an extreme example for me. I bought my first shares at $11, and they’ve appreciated roughly 60-fold since 2017. The return shown above is lower because I kept adding at higher prices rather than trimming as the stock rose.
Had I continually rebalanced AMD back toward its original weight, I would have systematically reduced my exposure to one of the best investments in the portfolio.
Your portfolio’s shape should reflect its performance over time.
Give your biggest winners room to run.
The Coffee Can approach makes even more sense when you look at how stock returns are actually distributed.
Blackstar Funds studied roughly 8,000 US stocks traded on the NYSE, AMEX, and Nasdaq from 1983 to 2006.
The most striking finding was that roughly 25% of stocks accounted for all of the market’s gains. The remaining 75%, collectively, contributed nothing.
The distribution underneath was brutal:
Around 40% of stocks lost money over their lifetimes.
Roughly one in five lost at least 75%.
And simply beating the market was rare:
64% underperformed the Russell 3000 over their lifetimes.
Only about 6% beat the index by more than 500%.
The lesson is uncomfortable but important: most stocks are not great long-term investments.
In a 20-stock portfolio, some will disappoint, and many will be merely average. Fewer than a handful may ultimately drive most of the return.
The problem is that you rarely know which ones in advance.
Selling a winner can mean trimming the very stock you needed most.
You only need a few great investments. The hard part is not getting in their way.
The secret to long-term investing lies in building a strategy you can stick with for decades, rather than guessing what the market will do next.
There will always be a reason to sell. A recession. A valuation scare. A new competitor. A market correction. But nobody knows what will happen next.
Long-term investing ultimately requires optimism that great businesses will keep adapting, growing, and creating value, despite the uncertainty.
Patience and persistence are among the most precious virtues in investing.
And you need both even if you are lucky enough to find the investment of a lifetime.
Sometimes the hardest thing is simply to leave a great investment alone.
Finding the winner is only the beginning. You have to let it get there.
That's it for today.
Happy investing!
Disclosure: I own AMD, ANET, AAPL, SHOP, and NVDA in App Economy Portfolio. I share my ratings (BUY, SELL, or HOLD) with App Economy Portfolio members.
Author's Note (Bertrand here 👋🏼): The views and opinions expressed in this newsletter are solely my own and should not be considered financial advice or any other organization's views.
2026-10-06 20:02:19
Welcome to the Premium edition of How They Make Money.
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In case you missed it:
OpenAI used DevDay last week to unveil more than 20 products and features. The most important announcement was Dots.
Dots are always-on AI agents with their own cloud computer, access to more than 4,000 apps, and the ability to keep working toward your goals even when you are not actively prompting them. Sam Altman described the shift as a “whole new way to work with AI” and a new set of “superpowers.”
The contrast with Meta Connect was striking. Meta showed Muse booking trips, shopping, and handling everyday tasks. OpenAI showed Dots managing projects, coding, preparing documents, coordinating across Slack and Teams, and helping run a startup.
For now, the two companies are attacking the agent market from opposite ends.
Meta is pushing toward AI for everyone.
OpenAI is starting with AI for high-value work.
And that difference may explain where ChatGPT is heading next.
Today at a glance:
The pieces start to fit together
OpenAI wants to become the operating layer
The business model gets more interesting
The cost of autonomy
Who owns the workday?
Some of the most interesting opportunities emerge in smaller, undercovered businesses that institutions and analysts barely follow.
I’m working on a new way to help you find them before they become obvious.
Spots will be strictly capped at launch.
OpenAI has spent the past year turning ChatGPT into much more than a chatbot, but the pieces have not always fit together cleanly.
ChatGPT started as the conversational interface.
Codex became the place for agentic coding, organized around projects and files.
ChatGPT Work extended that model to broader knowledge work, adding connections to SaaS apps and a persistent cloud environment.
More recently, OpenAI has started pulling those experiences into the same product.
The result is powerful, but increasingly complicated. You can have several projects, agents, threads, apps, and tasks running at once. At some point, the bottleneck becomes the person trying to keep track of it all.
That’s where Dots fit.
A Dot sits above your individual tools as a coordinating layer. It remembers what you are working on, follows projects over time, and can coordinate work across them. It acts like a control tower for your AI work.
The shift matters because the more work OpenAI hosts on its own cloud computers, the more persistent the relationship becomes. A chatbot conversation is relatively easy to move between providers. Recreating a collection of projects, files, permissions, preferences, and ongoing agents somewhere else is much harder.
In other words, Dots could make ChatGPT both easier to use and harder to leave.